Block diagonalization aided precoding algorithm for large MU-MIMO systems

Large Multi-User Multiple-Input Multiple-Output (MU-MIMO) system is considered as a potential technique to serve a high number of users simultaneously increasing the achievable data rates. By large we mean a large number of transmit antennas (Nt) at the base station (BS) and a large number of downlink user's terminals (UTs). In large MU-MIMO systems, the complexity of precoding algorithms becomes a bottleneck. In this work, we propose a low complexity precoder scheme with two steps. In the proposed scheme the UTs are classified into B blocks. Thereby, in the first step, the interference between block users block is mitigated using a Block Diagonalization (BD) method. In the second step, the interference between users belonging to the same block is palliated employing a more complex precoding. Simulation results show that the proposed scheme can achieve suitable performance while offering lower computational complexity than a nonlinear precoding.

[1]  Michele Zorzi,et al.  Communications Education and Training: Educational Services Board , 2016, IEEE Commun. Mag..

[2]  László Lovász,et al.  Factoring polynomials with rational coefficients , 1982 .

[3]  Emil Björnson,et al.  Massive MIMO: ten myths and one critical question , 2015, IEEE Communications Magazine.

[4]  Matti Latva-aho,et al.  An Efficient Channel Block Diagonalization Method for Generalized Zero Forcing Assisted MIMO Broadcasting Systems , 2011, IEEE Transactions on Wireless Communications.

[5]  Robert F. H. Fischer,et al.  Lattice-reduction-aided broadcast precoding , 2004, IEEE Transactions on Communications.

[6]  Martin Haardt,et al.  Zero-forcing methods for downlink spatial multiplexing in multiuser MIMO channels , 2004, IEEE Transactions on Signal Processing.

[7]  Wolfgang Utschick,et al.  Minimum Mean Square Error Vector Precoding , 2005, 2005 IEEE 16th International Symposium on Personal, Indoor and Mobile Radio Communications.

[8]  Martin Haardt,et al.  Generalized Design of Low-Complexity Block Diagonalization Type Precoding Algorithms for Multiuser MIMO Systems , 2013, IEEE Transactions on Communications.

[9]  Ning Wang,et al.  Per-antenna constant envelope precoding for secure transmission in large-scale MISO systems , 2015, 2015 IEEE/CIC International Conference on Communications in China (ICCC).

[10]  Robert W. Heath,et al.  Shifting the MIMO Paradigm , 2007, IEEE Signal Processing Magazine.

[11]  Robert W. Heath,et al.  Multi-Layer Precoding: A Potential Solution for Full-Dimensional Massive MIMO Systems , 2016, IEEE Transactions on Wireless Communications.

[12]  Robert F. H. Fischer,et al.  Precoding in multiantenna and multiuser communications , 2004, IEEE Transactions on Wireless Communications.

[13]  Yang Yang,et al.  QR decomposition and Gram Schmidt Orthogonalization based low-complexity multi-user MIMO precoding , 2014 .

[14]  Alberto González,et al.  An evaluation of precoding techniques for multiuser communication systems , 2010, 2010 7th International Symposium on Wireless Communication Systems.

[15]  Emil Björnson,et al.  Massive MIMO for Maximal Spectral Efficiency: How Many Users and Pilots Should Be Allocated? , 2014, IEEE Transactions on Wireless Communications.

[16]  Krishna Sayana,et al.  Downlink MIMO in LTE-advanced: SU-MIMO vs. MU-MIMO , 2012, IEEE Communications Magazine.

[17]  B. Sundar Rajan,et al.  A Low-Complexity Precoder for Large Multiuser MISO Systems , 2008, VTC Spring 2008 - IEEE Vehicular Technology Conference.

[18]  Yongming Huang,et al.  Improved nonlinear multiuser precoding using lattice reduction , 2009, Signal Image Video Process..

[19]  Timothy A. Thomas,et al.  LTE-advanced: next-generation wireless broadband technology [Invited Paper] , 2010, IEEE Wireless Communications.